Author: Abduramanova, Nezire Enverovna

Annotation: This article investigates the challenges of identifying and semantically tagging (annotating) cognitive metaphors within the "emotion" lexical-semantic field in Uzbek-English parallel corpora. Given that human emotions are inherently abstract, they are frequently materialized in language through figurative shifts and conceptual mappings (e.g., anger as fire, fear as ice). The primary objective of this study is to develop structural principles for unifying these cross-linguistically asymmetric metaphorical units into a systematic cognitive-semantic template within parallel corpus frameworks. Drawing upon J. Lakoff and M. Johnson’s Conceptual Metaphor Theory alongside corpus analysis methodologies, the paper proposes a novel, two-tier tagging model ([EMOT_TYPE + SRC_DOM]) designed for metaphorical emotional lexis. The findings enhance the accuracy of semantic data retrieval and sentiment analysis in natural language processing.

Keywords: conceptual metaphor, parallel corpus, semantic tagging, emotion field, target domain, source domain, cross-linguistic asymmetry.

Pages in journal: 603 - 606